论文标题
迈向长期自治：机器人学习的观点
Towards Long-term Autonomy: A Perspective from Robot Learning
论文作者
论文摘要
将来，预计服务机器人能够长时间自主操作，而无需人工干预。许多为这一目标而努力的工作一直在随着硬件和软件的开发而发展。今天，我们认为，长期机器人自主权的重要基础是机器人在现场和直立上学习的能力，尤其是当它们部署在不断变化的环境中或需要遍历不同的环境时。在本文中，我们从机器人学习的角度（尤其是在线方式）研究了长期自治的问题，并以其前提为“数据”和随后的“部署”。
In the future, service robots are expected to be able to operate autonomously for long periods of time without human intervention. Many work striving for this goal have been emerging with the development of robotics, both hardware and software. Today we believe that an important underpinning of long-term robot autonomy is the ability of robots to learn on site and on-the-fly, especially when they are deployed in changing environments or need to traverse different environments. In this paper, we examine the problem of long-term autonomy from the perspective of robot learning, especially in an online way, and discuss in tandem its premise "data" and the subsequent "deployment".
